The International Energy Agency report analyses global energy-related methane emissions, highlighting 124 million tonnes emitted in 2025. It examines abatement strategies, satellite data advancements and policy trends. The research underscores that 30% of emissions could be reduced at no net cost, advocating for robust international standards and increased transparency.

This handbook provides a harmonised framework for impact reporting on social bonds. It outlines core principles, recommendations, and sector-specific metrics for categories including affordable housing, essential services, and basic infrastructure. The document aims to enhance transparency and integrity in the social bond market through standardised reporting practices.

IBM Envizi Emissions is a data analytics platform and API that automates GHG Protocol-aligned emissions calculations. It enables organisations to integrate auditable ESG data into reporting workflows and performance management.

This research examines why climate-aligned guarantees often fail to mobilise private capital effectively. It identifies structural misalignments within multilateral development banks and suggests that strategic deployment requires a move towards portfolio-based approaches, local-currency financing, and better risk layering to address specific investment constraints in emerging markets.

This research evaluates the Paris Agreement ten years on, highlighting critical implementation and ambition gaps. It identifies a triple-track crisis involving geophysical inertia, cognitive barriers, and policy lags. The report proposes a precautionary paradigm using technological and financial levers to navigate climate uncertainty and prevent irreversible tipping points.

This report examines how artificial intelligence is transforming capital markets by shifting the industry from informational scarcity to analytical abundance. It introduces a structural framework involving capability, adoption, substitution, and recomposition, exploring alternative future states and the evolving nature of fiduciary accountability, market stability, and professional expertise.

This research analyses uncertainty in Network for Greening the Financial System (NGFS) climate scenarios across four vintages and 254 variables. It finds that revisions to initial conditions and model recalibration often exceed scenario and model uncertainty, requiring cautious interpretation in financial risk assessments.

This research evaluates the impacts of worker agency versus managerial discretion in employee recognition via an RCT in India. While worker democracy increased attendance by 11%, managerial discretion improved productivity by 6%. However, managerial control reduced work-related interactions, and worker voting encouraged collusion through reward sharing in exchange for votes.

This research assesses firm-specific amenity valuations using discrete choice experiments linked to German administrative records. It finds that amenities widen between-firm inequality by 20% in variance terms. Furthermore, gender differences in valuations contribute to female sorting into lower-wage firms, as women prioritise non-wage attributes more highly.

This research provides international data on firm-level artificial intelligence adoption across the US, UK, Germany, and Australia. While current impacts on employment and productivity are small, senior executives predict a 1.4 per cent productivity boost and a 0.7 per cent reduction in employment over the next three years.

This research analyses industrial policies for the multi-stage electric vehicle supply chain. It evaluates consumer subsidies and local content requirements, finding that while protectionist measures expand domestic production, they can significantly increase costs and reduce overall adoption compared to unconditional subsidies that maximise scale economies.

Most listed equity managers now have a target. Fewer have a plan that shows how it will be met. By January 2024, 264 Net Zero Asset Managers signatories had had their targets reviewed. Method is no longer the hard part.

This research investigates AI-managed household portfolios, finding that large language models recommend undiversified portfolios concentrated in high-momentum, large-cap technology stocks. While returns may exceed market benchmarks, they do not provide abnormal returns when adjusted for risk characteristics. Recommendations are primarily driven by media attention rather than investment skill.

Research demonstrates that Large Language Models exhibit purpose-conditioned bias when informed of downstream tasks. Goal-aware prompting leads to in-sample overfitting and inflated performance before knowledge cutoffs. Results indicate that disclosing objectives compromises neutrality, necessitating the separation of measurement and evaluation in AI-assisted workflows to ensure statistical validity.

An addendum to the Disaster Resilience Scorecard for Cities, this tool helps local governments assess and strengthen extreme heat risk management. It uses 18 indicators to evaluate governance, infrastructure, and financial planning to build long-term urban resilience against rising temperatures.

Global Nature Watch is an AI-powered Earth monitoring platform developed by the World Resources Institute and Google. It provides near-real-time data on land-use changes across various ecosystems to support nature-based risk assessment and environmental reporting.